Machine learning

BitHash: An efficient bitwise Locality Sensitive Hashing method with applications

Locality Sensitive Hashing has been applied to detecting near-duplicate images, videos and web documents. In this paper we present a Bitwise Locality Sensitive method by using only one bit per hash value (BitHash), the storage space for storing hash …

A cooperative coevolution-based Pittsburgh learning classifier system embedded with memetic feature selection

Given that real-world classification tasks always have irrelevant or noisy features which degrade both prediction accuracy and computational efficiency, feature selection is an effective data reduction technique showing promising perfor- mance. This …

A Fuzzy Timed Object-Oriented Petri Net for Multi-Agent Systems

In this paper, a multi-agent system (MAS) modeling method called fuzzy timed object-oriented Petri nets (FTOPN) is proposed. FTO-PN has extended Petri nets (PN) supporting object-oriented modeling and temporal fuzzy learning based on timed …

A Novel Chamber Scheduling Method in Etching Tools Using Adaptive Neural Networks

Chamber scheduling in etching tools is an important but difficult task in integrated circuit manufacturing. In order to effectively solve such combinatorial optimization problems in etching tools, this paper presents a novel chamber scheduling …